Aryan Garg

For the summer of '24, I'm interning at the Computational Behaviour Lab directed by Prof. Antti Oulasvirta at Aalto University. I'm extremely fortunate to have close support from Dr. Yue Jiang.

Last, I was a Bosch AI Research Fellow at the Computational Imaging Lab directed by Prof. Kaushik Mitra at the Indian Institute of Technology, Madras. In a past life, I finished my Bachelor's in Computer Science at IIT Mandi, where I was advised by Prof. Renu Rameshan. During my junior year, I had the privilege of being advised by Prof. Jean-François Lalonde and Dr. Yannick Hold-Geoffroy while spending a MITACS summer at Université Laval in the beautiful Quebec City.

Apart from research and academic services, I enjoy reading 📚, traveling ✈️, competing in endurance sports 🚴‍♂️, and trekking 🏔️. My previous trek (8th) was Sandakphu-Phalut in the Himalayas overlooking the majestic sleeping Buddha.

Email  /  CV  /  Scholar  /  Github  /  Kaggle

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Research Interests

My main focus is on deep generative modeling and 3D scene reconstruction. Outside of that, I also enjoy going on side quests 🗡️ to push the boundaries of core machine learning.

News

  • Jun-3, 2024 Interning this summer with Prof. Antti Oulasvirta at Aalto, Finland.
  • May-16, 2024 Won a grant for CILAB worth 30,000 USD from ISRO to develop a rocket launch 3D visualization module.
  • Apr-15, 2024 Accepted to PhD programmes at UW Madison, Rice University and KAUST.
  • Nov-1, 2023 Awarded the Post-Bacc. Bosch AI Fellowship (RBCDSAI, IIT Madras)
  • Jun-12, 2024 Joined CILab directed by Prof. Kaushik Mitra at IIT Madras.
  • Jun-1, 2023 Graduated from IIT Mandi with Bachelors in CS.
  • June 2022 Won the MITACS Award. Interning this summer with Prof. Jean Francois Lalonde at ULaval, Canada.

Publications

HDRSplat: Gaussian Splatting for High Dynamic Range 3D Scene Reconstruction from Raw Images
Shreyas Singh*, Aryan Garg*, Kaushik Mitra
BMVC, 2024   🇬🇧
Project Page / arXiv

High Dynamic Range 3D Gaussian Splatting At Night

Stereo-Knowledge Distillation from dpMV to Dual Pixels for Light Field Video Reconstruction
Aryan Garg, Raghav Mallampali, Akshat Joshi, Shrisudhan Govindarajan, Kaushik Mitra
ICCP, 2024   🇨🇭
GitHub / arXiv

Stereo Knowledge Distillation for dp-disparity estimation, dpMV dataset, and LFVR.

Parameter and Data Efficient Spectral Style DCGAN
Aryan Garg
ICLR Tiny Paper,2024   Oral Presentation   🇦🇹
GitHub / arXiv / OpenReview

Unconditional face generation at the speed and size of DCGAN using a relatively tiny training dataset (~4000). Convergence and higher fidelity over StyleGAN are achieved using a spectrally normalized discriminator and a tiny generator within 20 minutes on a commercial, free cloud GPU.

G-PECNet: Towards a Generalizable Pedestrian Trajectory Prediction System
Aryan Garg, Renu Rameshan
ICLR Tiny Paper, 2024   Oral Presentation   🇦🇹
GitHub / arXiv / OpenReview

Synthetic dataset generation and sinusoidal activations lead to a winning solution over the final displacement error.

Re-envisioning Sky Models
Ian J. Maquignaz, Lucas Valença, Aryan Garg, Yannick Hold Geoffroy, Julien Philip, Jean Francois Lalonde
Semaine numériQC, 2023   🇨🇦
3rd Best Presentation Award

SkyNet for user-controlled generation of skies incorporating the versatility of parametric models and realism from deep generative networks.

DeepSky
Ian J. Maquignaz, Aryan Garg, Yannick Hold Geoffroy, Julien Philip, Jean Francois Lalonde
Symposium IA Montréal, 2022   🇨🇦
Poster / Abstract

DeepSky: Learning to generate photorealistic skies per user-controlled positioning of solar and atmospheric components

Academic Services

Reviewer For:

  • (ICVGIP) 14th Indian Conference on Computer Vision, Graphics and Image Processing, 2023
  • (ICLR) International Conference on Learning Representations Tiny Papers, 2024
  • (CVPR-W) Computer Vision and Pattern Recognition - Workshop: AI for Content Creation, AI4CC 2024

Teaching Assistant

  • CS208 - Mathematical Foundations of Computer Science (Prof. Samar Agnihotri) - Fall ’21 IIT Mandi
  • EE522 - Matrix Theory for Engineers (Prof. Renu Rameshan) - Fall ’21 IIT Mandi
  • EE5719 - Deep Learning for Imaging (Prof. Kaushik Mitra) - Fall ’23 IIT Madras (NPTEL)

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